CoreLogic · 5 hours ago

Senior Data Engineer

Irvine, CA

Full-time

Remote

Senior Level

$106K/yr - $150K/yr

5+ years exp

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Responsibilities

Orchestrate, deploy, and manage data pipelines for varied data and data science projects across SQL, Python, and GCP environments

Collaborate with technical product managers, data scientists, and analysts to ensure a deep understanding of product goals, business context, and key data needs

Develop data solutions that leverage big data technologies (e.g., Airflow, BigQuery, dbt, Google DataFlow, DataProc, Apache Beam) to support scalable, reliable, and innovative data products

Implement cloud resource provisioning, automation, and monitoring, primarily within GCP, to optimize system performance and security

Participate in technical product management efforts, with future opportunities to drive cross-functional projects that shape our data platform’s roadmap

Maintain detailed documentation of data processes, standards, and workflows, ensuring best practices in SDLC, data management, and project execution.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

SQLPythonGCPBig Data ToolsSparkHadoopKafkaMachine LearningDatabase DesignData Pipeline ManagementQuery OptimizationAgile MethodologiesDevOpsCI/CDInfrastructure as CodeGCP Cloud ArchitectGCP Data EngineerStakeholder EngagementDocumentation SkillsCross-Functional Collaboration

Required

Bachelor’s degree in computer science, Data Engineering, a related field or equivalent experience.

5+ years of experience in data engineering roles, with hands-on expertise in SQL, Python, and cloud services (GCP preferred).

Strong experience with big data tools such as Spark, Hadoop, and Kafka, with a deep understanding of cloud-based data storage, processing, and orchestration (e.g., Jenkins, Terraform)

Demonstrated ability to work cross-functionally and communicate effectively across technical and non-technical teams

Experience with working on machine learning (ML) engineering initiatives, with an understanding of data science and generative AI initiatives

Experience working with stakeholders to understand requirements and define execution plans for technical work

Experience working with large-scale data products, with strong documentation skills and the ability to translate complex requirements into actionable solutions

Ability to optimize database queries and query performance

Demonstrated expertise in a variety of the concepts, practices, and procedures in database design and implementation

Ability to mentor other team members on area(s) of expertise

Provide operational support on complex/escalated issues in order to diagnose and resolve incidents in production data pipelines

Proficiency in Agile methodologies, with knowledge of DevOps, CI/CD, and infrastructure as code practices